---
title: Atla
description: Integrate `Atla` with Agno for real-time monitoring, automated evaluation, and performance analytics of your AI agents.
---

[Atla](https://www.atla-ai.com/) is an advanced observability platform designed specifically for AI agent monitoring and evaluation. 
This integration provides comprehensive insights into agent performance, automated quality assessment, and detailed analytics for production AI systems.

## Prerequisites

- **API Key**: Obtain your API key from the [Atla dashboard](https://app.atla-ai.com)

Install the Atla Insights SDK with Agno support:

```bash
pip install "atla-insights"
```

## Configuration

Configure your API key as an environment variable:

```bash
export ATLA_API_KEY="your_api_key_from_atla_dashboard"
```

## Example

```python
from os import getenv
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from atla_insights import configure, instrument_agno

# Step 1: Configure Atla
configure(token=getenv("ATLA_API_KEY"))

# Step 2: Create your Agno agent
agent = Agent(
    name="Market Analysis Agent",
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[DuckDuckGoTools()],
    instructions="Provide professional market analysis with data-driven insights.",
    debug_mode=True,
)

# Step 3: Instrument and execute
with instrument_agno("openai"):
    response = agent.run("Retrieve the latest news about the stock market.")
    print(response.content)
```

Now go to the [Atla dashboard](https://app.atla-ai.com/app/) and view the traces created by your agent. You can visualize the execution flow, monitor performance, and debug issues directly from the Atla dashboard.

<Frame caption="Atla Agent run trace">
  <img
    src="/images/atla-trace-summary.png"
    style={{ borderRadius: '10px', width: '100%', maxWidth: '800px' }}
    alt="atla-trace"
  />
</Frame>